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Computation in Neural Circuits

Investigation of mechanisms underlying neural computation through the development of models on the level of networks of spiking neurons. This group applies a predominantly top-down approach to discover functional constraints on structure, plasticity and dynamics, particularly with respect to learning and memory. Secondary focus on simulation technology for high-performance computers.

The group of Abigail Morrison in the Laboratory for Computational and Systems Neuroscience studies models of cognitive functions with a particular focus on implicit learning processes. Starting from assumptions about the computational function of a neural circuit, the group develops biologically constrained spiking neural network models to discover the requirements on the circuit structure, dynamics, and plasticity to realize the function in question.

Simulation studies involving plasticity are computationally expensive and often require long simulation times to cope with transients in the dynamics. The group therefore develops simulation techniques for massively parallel computers that are efficient in terms of both computation and memory consumption. NEST